A nonlinear dynamic inversion-based neurocontroller for unmanned combat aerial vehicles during aerial refuelling

Pedro, J. O.; Panday, A.; Dala, L.

Artykuł - szczegóły

Tytuł artykułu

A nonlinear dynamic inversion-based neurocontroller for unmanned combat aerial vehicles during aerial refuelling

Autorzy

Pedro J. O. , Panday A. , Dala L.

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

Warianty tytułu

Języki publikacji

Abstrakty

The paper presents the development of modelling and control strategies for a six-degree-of-freedom, unmanned combat aerial vehicle with the inclusion of the centre of gravity position travel during the straight-leg part of an in-flight refuelling manoeuvre. The centre of gravity position travel is found to have a parabolic variation with an increasing mass of aircraft. A nonlinear dynamic inversion-based neurocontroller is designed for the process under investigation. Three radial basis function neural networks are exploited in order to invert the dynamics of the system, one for each control channel. Modal and time-domain analysis results show that the dynamic properties of the aircraft are strongly influenced during aerial refuelling. The effectiveness of the proposed control law is demonstrated through the use of simulation results for an F-16 aircraft. The longitudinal neurocontroller provided interesting results, and performed better than a baseline nonlinear dynamic inversion controller without neural network. On the other hand, the lateral-directional nonlinear dynamic inversion-based neurocontroller did not perform well as the longitudinal controller. It was concluded that the nonlinear dynamic inversion-based neurocontroller could be applied to control an unmanned combat aerial vehicle during aerial refuelling.

Słowa kluczowe

trim analysis stability analysis neurocontroller UCAV aerial refuelling nonlinear dynamic inversion

analiza stateczności inwersja dynamiczna

Wydawca

Oficyna Wydawnicza Uniwersytetu Zielonogórskiego

Czasopismo

International Journal of Applied Mathematics and Computer Science

Rocznik

2013

Tom

Vol. 23, no. 1

Strony

75--90

Opis fizyczny

Bibliogr. 56 poz., rys., tab., wykr.

Twórcy

autor

Pedro J. O.

Jimoh.Pedro@wits.ac.za

School of Mechanical, Aeronautical and Industrial Engineering, University of the Witwatersrand, 1 Smuts Avenue, Johannesburg, South Africa

autor

Panday A.

PandayA@caa.co.za

School of Mechanical, Aeronautical and Industrial Engineering, University of the Witwatersrand, 1 Smuts Avenue, Johannesburg, South Africa

autor

Dala L.

Laurent.dala@wits.ac.za

School of Mechanical, Aeronautical and Industrial Engineering, University of the Witwatersrand, 1 Smuts Avenue, Johannesburg, South Africa

Bibliografia

[1] Bajodah, A.H. (2009). Generalised dynamic inversion spacecraft control design methodologies, IET Control Theory and Applications 3(2): 239–251.
[2] Battipede, M., Napolitano, P., Perhinschi, M.G., Massotti, L. and Lando, M. (2003). Implementation of an adaptive predictor-corrector neural controller within the NASA IFCS F-15 WVU simulator, Proceedings of the American Control Conference, Denver, CO, USA, pp. 1302–1307.
[3] Bishop, C.M. (1995). Neural Networks for Pattern Recognition, Oxford University Press, Oxford.
[4] Clark, R.M. (2000). Uninhabited Combat Vehicles: Airpower by the People, For the People, But Not with the People, Air University Press, Maxwell Air Force Base, AL.
[5] Dell’Aquila, R.V., Napolitano, M.R. and Mammarella, M. (2007). Realtime machine-vision-based position sensing system for UAV aerial refueling, Journal of Real-Time Image Processing 1(3): 213–224.
[6] Deng, J., Becerra, V.M. and Stobart, R. (2009). Input constraints handling in an MPC/feedback linearization scheme, International Journal of Applied Mathematics and Computer Science 19(2): 219–232, DOI: 10.2478/v10006-009-0018-2.
[7] Dogan, A. and Kim, E. (2007). Control and simulation of relative motion for aerial refueling in racetrack manoeuvres, Journal of Guidance, Control and Dynamics 30(5): 1551–1557.
[8] Dogan, A., Sato, S. and Blake, W. (2005). Flight control and simulation for aerial refuelling, Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, San Francisco, CA, USA, Paper 2005-6264, pp. 1–15.
[9] Dufrene, W.R. (2004). AI techniques in uninhabited aerial vehicle flight, IEEE Aerospace and Electronic Systems Magazine 19(8): 8–12.
[10] Elliot, C.M. and Dogan, A. (2010). Investigating nonlinear control architecture options for aerial refueling, Proceedings of the AIAA Atmospheric Flight Mechanics Conference, Toronto, Canada, Paper 2010-7927.
[11] Eshel, T. (2004). Extending the F-16 range, Defense update, International Online Defense Magazine 1, http://www.defense-update.com/products/f/f-16-fuel.html.
[12] Etkin, B. and Reid, L.D. (1996). Dynamics of Flight: Stability and Control, John Wiley and Sons Inc., New York, NY.
[13] Fravolini, M.L., Ficola, A., Napolitano, M.R., Campa, G. and Perhinschi, M. G. (2003). Development of modelling and control tools for aerial refuelling for UAVs, Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, TX, USA, Paper 2003-5798.
[14] Gili, A.P. and Battipede, M. (2001). Adaptive neurocontroller for a nonlinear combat aircraft model, Journal of Guidance, Control and Dynamics 24(5): 910–917.
[15] Hagan, M.T. and Demuth, H.B. (1999). Neural networks for control, Proceedings of the American Control Conference, San Diego, CA, USA, pp. 1642–1656.
[16] Hansen, J., Murray, J.E. and Campos, N.V. (2004). The NASA Dryden AAR project: A flight test approach to an aerial refueling system, Proceedings of the AIAA Atmospheric Flight Mechanics Conference, Providence, RI, USA, Paper 2004-4939.
[17] Haykin, S. (1999). Neural Networks. A Comprehensive Foundation, 2nd Edn., Prentice-Hall, Englewood Cliffs, NJ.
[18] Ito, D., Georgie, J., Valasek, J. and Ward, D.T. (2002). Reentry vehicle flight controls design guidelines: Dynamic inversion, Technical report, NASA Technical Paper NASA/TP 2002-210771, Flight Simulation Laboratory, Huston, TX.
[19] Jin, Z., Shima, T. and Schumacher, C.J. (2006). Optimal scheduling for refuelling multiple autonomous aerial vehicles, IEEE Transactions on Robots 22(4): 682–693.
[20] Kamalasadan, S. and Ghandakly, A.A. (2011). A neural network parallel adaptive controller for fighter aircraft pitch-rate tracking, IEEE Transactions on Instrumentation and Measurement 60(1): 258–267.
[21] Kaneshige, J.T., Bull, J. and Totah, J.J. (2000). Generic neural flight control and autopilot system, Proceedings of the AIAA Guidance, Navigation, and Control Conference, Denver, CO, USA, Paper 2000-4281.
[22] Khanafseh, S.M. and Pervan, B. (2007). Autonomous airborne aerial refueling of unmanned air vehicles using the global position system, Journal of Aircraft 44(5): 1670–1682.
[23] Koch, A. (2005). How to aerial refuel the F-16, http://www.virtualtigers.com/htm/refuel.html.
[24] Kung, C.-C. (2008). Nonlinear H-infinity robust control applied to F-16 aircraft with mass uncertainty using control surface inverse algorithm, Journal of the Franklin Institute 345(6): 851–876.
[25] Lane, S.H. and Stengel, R.F. (1988). Flight control design using non-linear inverse dynamics, Automatica 24(4): 471–483.
[26] Lee, S., Ha, C. and Kim, B.S. (2005). Adaptive nonlinear control system design for helicopter robust command augmentation, Aerospace Science and Technology 9(3): 241–251.
[27] Li, Y., Sundararajan, N. and Saratchandran, P. (2001). Neuro-controller design for nonlinear fighter aircraft manoeuvre using fully tuned RBF networks, Automatica 37(8): 1293–1301.
[28] Lombaerts, T.J.J., Chu, Q.P., Mulder, J.A. and Joosten, D.A. (2011). Modular flight control for reconfiguration design and simulation, Control Engineering Practice 19(6): 540–554.
[29] MacKunis, W., Patre, P.M., Kaiser, M.K. and Dixon, W.E. (2010). Asymptotic tracking for aircraft via robust and adaptive dynamic inversion methods, IEEE Transactions on Control Systems Technology 18(6): 1448–1456.
[30] Mammarella, M., Campa, G., Napolitano, M.R. and Fravolini, M.L. (2008). Comparison of point matching algorithms for the UAV aerial refueling problem, Machine Vision and Applications 1(3): 213–224.
[31] Mao, W. and Eke, F.O. (2008). A survey of the dynamics and control of aircraft during aerial refueling, Nonlinear Dynamics and Systems Theory 8(4): 375–388.
[32] McFarland, M.B. and Calise, A.J. (2000). Adaptive nonlinear control of agile antiair missiles using neural networks, IEEE Transactions on Control Systems Technology 8(5): 749–756.
[33] McLean, D. (1990). Automatic Flight Control Systems, Prentice Hall, New York, NY.
[34] Morelli, E.A. (1998). Global nonlinear parametric modeling with application to F-16 aerodynamics, Technical report, Dynamics and Control Branch, NASA Langley Research Centre, Hampton, VA.
[35] Nabney, I.T. (2002). NETLAB: Algorithms for Pattern Recognition, Springer, London.
[36] Ochi, Y. and Kominami, T. (2005). Flight control for automatic aerial refuelling via PNG and LOS angle control, Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, San Francisco, CA, USA, Paper 2005-6268, pp. 1–11.
[37] Ollero, A. and Merino, L. (2004). Control and perception techniques for aerial robotics, Annual Reviews in Control 28(2): 167–178.
[38] Pachter, M., Houpis, H. and Trosen, D.W. (1997). Design of an air-to-air automatic refueling flight control system using quantitative feedback theory, International Journal of Robust and Nonlinear Control 7(3): 561–580.
[39] Pardesi, M.S. (2005). Unmanned aerial vehicles-unmanned combat aerial vehicles: Likely missions and challenges for the policy-relevant future, Air and Space Power Journal 19(3): 45–54.
[40] Pashikar, A.A., Sundararajan, N. and Saratchandran, P. (2007). Adaptive nonlinear neural controller for aircraft under actuator failures, Journal of Guidance, Control and Dynamics 30(3): 835–847.
[41] Pedro, J.O. (1992). Numerical Simulations of Transport Aircraft in Variable Wind Field, Ph.D. thesis, Faculty of Mechanical, Power and Aeronautical Engineering, Warsaw University of Technology, Warsaw, (in Polish, unpublished).
[42] Pedro, J.O. and Bigg, C.G. (2005). Development of a flexible embedded aircraft/Control system simulation facility, Proceedings of the AIAA Modeling and Simulation Technologies, Conference and Exhibit, San Francisco, CA, USA, pp. 1–25.
[43] Pollini, L., Campa, G., Giulietti, F. and Innocenti, M. (2003). Virtual simulation set-up for UAVs aerial refuelling, Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Austin, TX, USA, Paper 2003-5682, pp. 1–8.
[44] Reiner, J., Balas, G.J. and Garrard, W.L. (1996). Flight control design using robust dynamic inversion and time scale separation, Automatica 32(11): 1493–1504.
[45] Soares, F., Burken, J. and Marwala, T. (2006). Neural network applications in advanced aircraft flight control system, a hybrid system, a flight test demonstration, in I. King, J. Wang, L-W. Chan and D. Wang (Eds.) Neural Information Processing, Lecture Notes in Computer Science, Vol. 4234, Springer-Verlag, Berlin/Heidelberg, pp. 684–691.
[46] Spaulding, C.M., Mansur, H.M., Tischler, M.B., Hess, R.A. and Franklin, J.A. (2005). Nonlinear inversion control for a ducted fan UAV, Proceedings of the AIAA Atmospheric Flight Mechanics Conference and Exhibit, San Francisco, CA, USA, pp. 1–26.
[47] Steinberg,M.L. (2001). Comparison of intelligent, adaptive, and nonlinear flight control laws, Journal of Guidance, Control and Dynamics 24(4): 693–699.
[48] Stengel, R.F. (2004). Flight Dynamics, Princeton University Press, Princeton, NJ.
[49] Steven, B.L. and Lewis, F.L. (1992). Aircraft Control and Simulation, John Wiley and Sons Inc., New York, NY.
[50] Thompson, K.E. (1998). F-16 uninhabited air combat vehicles, Technical report, Air Command and Staff College, Air University, Maxwell Air Force Base, AL.
[51] Vendra, S., Campa, G., Napolitano, M.R., Mammarella, M., Fravolini, M.L. and Perhinschi, M.G. (2007). Addressing corner detection issues for machine vision based UAV aerial refuelling, Machine Vision and Applications 18(5): 261–273.
[52] Waishek, J., Dogan, A. and Blake, W. (2009). Derivation of the dynamics equations of receiver aircrft in aerial refueling, Journal of Guidance, Control and Dynamics 32(2): 586–598.
[53] Wang, J., Patel, V.V., Cao, C. and Hovakimyan, N. (2008). Novel L1 adaptive control methodology for aerial refueling with guaranteed transient performance, Journal of Guidance, Control and Dynamics 31(1): 182–193.
[54] Wilson, J.R. (2005). UAV worldwide roundup 2005, Aerospace America 43(9): 26–31.
[55] Withrow, M. (2004). UAV automated aerial refuelling: one step closer to reality, Air Vehicles Directorate News AFRL Magazine.
[56] Wong, K. and Bill, C. (1998). UAVs over Australia—market and capabilities, 13th Bristol International Conference on RPVs/UAVs, Bristol, UK.

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-31838fa8-ced3-42b1-9124-16a40c195d32